Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …

Deviation from a normal facial shape and symmetry can arise from numerous sources,
including physical injury and congenital birth defects. Such abnormalities can have …

Speech-driven 3D talking heads generation has emerged as a significant area of interest
among researchers, presenting numerous challenges. Existing methods are constrained by …

The diffeomorphic registration framework enables one to define an optimal matching
function between two probability measures with respect to a data-fidelity loss function. The …

Abstract 3D generative modeling is accelerating as the technology allowing the capture of
geometric data is developing. However, the acquired data is often inconsistent, resulting in …

Deformable Image registration is a fundamental yet vital task for preoperative planning,
intraoperative information fusion, disease diagnosis and follow-ups. It solves the non-rigid …

Surface mapping is used in various brain imaging studies, such as for mapping gray matter
atrophy patterns in Alzheimer's disease. Riemannian metrics on surface (RMOS) is a state-of …

Generating speech-driven 3D talking heads presents numerous challenges; among those is
dealing with varying mesh topologies. Existing methods require a registered setting, where …

This work introduces a new Riemannian optimization method for registering open
parameterized surfaces with a constrained global optimization approach. The proposed …

Diffeomorphic registration frameworks such as large deformation diffeomorphic metric
mapping (LDDMM) are used in computer graphics and the medical domain for atlas …